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15-462 Project 4: Photon Mapping

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15-462 Project 4: Photon Mapping 15-462 Project 4: Photon Mapping Release Date: Thursday, April 9 2009 Due Date: Thursday, April 30, 2009 at 23:59:59 Starter Code: http://www.cs.cmu.edu/~15462/proj/04/p4.tar.gz 1 Overview In the third project, you learned about global illumination models and wrote a ray tracer that was able to render certain natural phenomena that could not be rendered (at least without much effort) with OpenGL. For this project, we will be taking your ray tracer and using it as the starting point for a basic photon mapper into order to achieve a caustic effect. If you have not completed the minimum requirements for project 3, your first priority should be to finish those requirements. As mentioned during lecture, we will return half-credit to any requirements for project 3 that you complete for project 4. Note that you must have ray casting, refraction, reflection, and color compu- tation correct in order to see any results at all. Without these working correctly, it is very unlikely you will see reasonable results. However, you can still write the code for project 4 since we grade code more than results, but do not expect to get any results. As in project 3, this assignment is code intensive and will require you to make design decisions about how you wish to code it. Since the textbook is unfortunately a poor resource for this assignment, you will want to use the slides from lecture as well as some resources that we provide you to give you more information on the topic. The slides from Lecture 17 contain an overview of the material as well as some insight in the steps you will need to take to structure your code. The slides from Lecture 14 might be useful when thinking about your kd-tree. We also will provide some links to useful resources and papers at the end of this document. 1.1 Submission Process Your handin directory may be found at /afs/cs.cmu.edu/academic/class/15462- s09-users/andrewid/p4/ You should submit the entire contents of the handout, your modified files, and any screen shots in this directory. 1 To test your code, we will simply cd into the directory, then run make clean; make. Therefore, your code should should be placed in the root directory un- compressed (i.e. the makefile’s absolute path should be .../15462-s09-users/andrewid/p3/Makefile.). DO NOT submit a com- pressed file or binary files. So, if you made it on Windows, delete the Debug and Release folders, and if you made it on a Unix system, run make clean before submitting. In addition, you must fill out the p4.txt file in the handout, describing which features you have implemented for project 4, and which you have not. In partic- ular, if you have missing features, be sure to explain how much you accomplished and why. If you did extra work, be sure to explain what that was and how you did it. Furthermore, you should detail anything you think we need to know to understand your code. Regardless of what machine you use to code your assignment, it must compile and run correctly on the machines in the Wean 5336 cluster. There are a lot of students in the course and only 25 machines, so you probably don't want to wait until the last minute to test it, even more so because you will want a substantial amount of time to render your scenes. By university policy, we can only accept assignments through Friday, May 1, 17:00. Therefore, you may not use late days on project 4. 2 Handout/Requirements 2.1 Required Tasks Please note that the purpose of this assignment is to try and achieve a particular effect. We are not grading you on how close your screen shots match those from the reference shots; due to the probabilistic nature of the photon mapping algorithm, your screen shots may appear to be different. The reference shots will provide a good reference about where the caustics should be located, but you do not need to be concerned about matching them perfectly. It's more about getting a rough approximation of the effect. • Define photons • Implement a kd-tree as your photon map and provide functionality to properly construct it and insert photons. • Implement nearest-neighbor search for your photon map • Fire photons at the Scene::caustic generator object in your scene and store them in your photon map. • Properly calculate the radiance estimate and recalculate color properly. • Support scenes 0 and 1. Note that due to complexity, we do not require you support scene 2, the pool scene. But you may explore using photon mapping on it if you wish. 2 2.2 Extra Credit See section 8.1 for information about possible extra-credit ideas. 2.3 Files to Update/Edit The handout for project 3 includes the following files: • staffldr.cpp Note: You will probably want to create a new file for you photon mapping code that will hold any classes any functions you may need for photon mapping. You will likely also modify raytrace.cpp to integrate the photon mapper. 3 Photon Mapping Before we begin, here is a quick refresher on the photon mapping algorithm and how our project uses it. Photon mapping is an alternative global illumination model that attempts to provide a solution to the rendering equation. Like ray tracing, photon mapping can be considered a "point-sampling" model, that is, colors are evaluated at points as opposed to surfaces. However, photon mapping provides computational speedups over other prominent point-sampling models such as path tracing and Metropolis Light Transport. The general photon mapping approach is a two-pass algorithm. In the first pass, or photon tracing step, photons are emitted from all lights in the scene and are bounced around until they are eventually absorbed somewhere in the scene. Information about each photon is then stored in a map, the photon map, which is generally a spatial data structure optimized for fast insertions and lookups. Normally, there are two photon maps created: one for overall global illumination and one specifically for caustics. In the second pass, color at each point is computed by breaking the ren- dering equation into terms: direct illumination, specular reflection, caustics, and indirect illumination. The summation of these terms returns the color at each point. The first two terms can be solved using just ray tracing. Caustics are handled by computing an estimate of the radiance at a given point using the caustics photon map. Likewise, indirect illumination can be calculated by computing another radiance estimate using the global photon map. We are not requiring you to implement the full photon mapping algorithm. You are only implementing a rough simplication of it. We will be taking your ray tracer from project 3 and extending it to compute caustics for a single specular object per scene. Therefore, instead of two photon maps, you will be constructing only one photon map for caustics. 3 4 Photons Photons are very similar to rays in behavior in that we will be firing them into our scene in the same manner we fired rays in the ray tracer. However, they carry different information. Whereas the point of eye rays are to return a color from the destination point, the point of photons are to carry a color to the destination point to later be used in a radiance estimate. A photon is basically a unit of light at a given position. It is born at the position of the light and is fired into the scene where it goes through repeated bounces off any number of objects until some termination criteria is reached. For this project, you will be firing photons at specular objects and terminating them once they hit a diffuse surface. We impose no restrictions on how you represent photons, though there are a few required elements and a few considerations to bear in mind. The need for each element will be explained in later sections. You will, at a minimum, need to store: • The position of the photon (at its final destination point). • The intensity of the photon as an RGB color. • The incidence angle of the photon. It is the direction of the ray when the photon hits its destination surface. Since you be storing at least several thousand in memory simultaneously, pho- tons should be as compact as possible. You may also wish to consider storing them in a contiguous array rather than allocating each separately. 5 The Photon Map and Kd-Tree 5.1 Photon Map Once we emit all our photons (see section6), we store them in a map for retrieval during our radiance estimate (see section 7.1). This is called the photon map. Since it's holding several thousand or more photons, we want this to be as efficient a data structure as possible. The two operations we must support are insertion and retrieving the n nearest photons to any point, for any n. 5.2 The Kd-tree The data structure we would like you to implement for this assignment is a kd- tree. Recall that a kd-tree is much better than either a grid or an octree because in general, our distribution of photons in our scene is not uniform (especially in the case for caustics). A kd-tree allows us to create a balanced tree to improve look up times. A kd-tree is a binary tree that partitions space along each dimension (in our case, 3).
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